This disclosure relates to image processing methods and systems for generating and reviewing redacted video of a scene. More specifically, this disclosure, and the exemplary embodiments described herein, relates to the generation of redacted video where objects detected within a video are obfuscated or removed based on probability based analysis, and relates to a manual review of the redacted video where a manual review process is augmented to provide a variable playback speed of the redacted video based on the probability-based analysis associated with the detected objects.
With increasing vast collections of surveillance video, body worn cameras and private videos, video redaction technology has become very important and is currently an expensive process. Freedom of Information Act (FOIA) laws require government agencies to release video upon request while it must maintain certain degrees of privacy. Video redaction includes the obfuscation or removal of personal information in videos for privacy protection. Two primary steps in a visual redaction system are localization of object(s) to be redacted and obfuscation or removal of the object. Completely automated detection and obfuscation has too many false negatives (missed redactions) for law enforcement to simply input a requested video and release the output. Existing tools marketed to law enforcement have minimal automation, primarily using manual object tagging by a skilled technician in combination with some automated tracking of the objects. These existing tools involve a manual review of every frame to ensure that the identity of a person or sensitive object is not exposed which is a time consuming and expensive process.
Provided herein are automated methods and systems to generate redacted video and augment a manual review process of the redacted video to increase the efficiency and/or accuracy of the reviewer.